DreamNet: A Deep Riemannian Network based on SPD Manifold Learning for Visual Classification. (arXiv:2206.07967v1 [cs.CV])

Web: http://arxiv.org/abs/2206.07967

Image set-based visual classification methods have achieved remarkable
performance, via characterising the image set in terms of a non-singular
covariance matrix on a symmetric positive definite (SPD) manifold. To adapt to
complicated visual scenarios better, several Riemannian networks (RiemNets) for
SPD matrix nonlinear processing have recently been studied. However, it is
pertinent to ask, whether greater accuracy gains can be achieved by simply
increasing the depth of RiemNets. The answer appears to be negative, as deeper
RiemNets tend to lose …

arxiv classification cv deep learning manifold network on